Forecasting Implications of the Recent Decline in Infl ation. Federal Reserve Bank of Cleveland, Economic Commentary
Bibliographic record
Abstract
Should the unanticipated slowing of infl ation that has occurred since early 2012 raise doubts about the reliability of infl ation forecasts? We answer this question by conducting a few exercises with a common macroeconomic forecasting model. Our results indicate that even though infl ation turned out to be much lower than forecasted, it still fell well within a normal range of uncertainty, and most of the deviation from the original forecast was a response to other economic developments. ISSN 0428-1276 Many observers have been surprised by the decline in consumer price infl ation that has occurred since early 2012. At that time, the Federal Open Market Committee (FOMC) projected that both overall and core PCE infl ation would be about 1.7 percent in 2013.1 Today, though, these measures of infl ation stand at about 1.2 percent. PCE infl ation this year has also come in well below the projections of private-sector economists captured in the February 2012 Survey of Professional Forecasters (SPF).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.013 | 0.008 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".